public void LookupFalseTest()
{
GroundTruth.CreateGroundTruthLookup();
string[] imageArray = GroundTruth.GetImageKeys();
bool isHealthy = GroundTruth.Lookup("DSC00041.JPG");
Assert.IsFalse(isHealthy);
}
public void GetImageKeysTest()
{
GroundTruth.CreateGroundTruthLookup();
string[] imageArray = GroundTruth.GetImageKeys();
int numEntries = imageArray.Length;
int numPictures = 1787;
Assert.IsTrue(numEntries == numPictures);
}
/// <summary>
/// This is the starting point of the server program. Here we assign the app a configuration and initialize Machine Learning engines.
/// </summary>
/// <param name="configuration">An IConfiguration object</param>
public Startup(IConfiguration configuration)
{
Configuration = configuration;
// Set Firebase URL:
RestfulDBConnection.FIREBASE_URL = Configuration["FirebaseURL"];
// Initialize Machine Learning Components:
MLModel.CreatePredictionEngine();
GroundTruth.CreateGroundTruthLookup();
// Get the Machine Learning Warmed Up:
MLModel.Predict("https://firebasestorage.googleapis.com/v0/b/agricultureai-15ce0.appspot.com/o/DSC00025.JPG?alt=media");
}
public void getNumTrueAndFalse()
{
int numTrue = 0;
int numFalse = 0;
GroundTruth.CreateGroundTruthLookup();
string[] imageArray = GroundTruth.GetImageKeys();
int numImages = imageArray.Length;
for (int i = 0; i < imageArray.Length; i++)
{
if (GroundTruth.Lookup((imageArray[i]).ToString()) == true)
{
numTrue++;
}
else
{
numFalse++;
}
}
Assert.IsTrue((numFalse + numTrue) == numImages);
}